Database query interface extension for machine learning algorithms in business intelligence applications

Abstract

A computer system includes a processor, a file system having a query application and a query interface, a database, and a query interface extension executing on the processor. The database includes a plurality of business intelligence (BI) data objects. Each of the BI data objects is associated with one or more data parameters. The query interface extension intercepts a data call from the query application to the query interface for data corresponding to one or more of the BI data objects. The data call includes one or more selected parameters. The data call is parsed to ascertain the one or more selected parameters. Data corresponding to the one or more BI data objects is obtained from the database based on the one or more selected parameters. A data prediction result is appended to the obtained data.

What is claimed is: 
     
       1. A computer system comprising:
 a processor; 
 a memory coupled to the processor, the memory storing thereon a file system having a query application and a query interface; 
 a database storing a plurality of business intelligence (BI) data objects, each BI data object being associated with one or more data parameters; and 
 a query interface extension executing on the processor, the query interface extension configured to:
 intercept a data call from the query application to the query interface for data corresponding to one or more of the BI data objects, wherein the data call includes one or more selected parameters; 
 parse the data call to ascertain the one or more selected parameters; 
 obtain the data corresponding to the one or more BI data objects based on the one or more selected parameters; and 
 append a prediction result to the obtained data. 
 
 
     
     
       2. The computer system in accordance with  claim 1  further comprising:
 one or more prediction models; and 
 a machine learning execution tool executing on the processor and electronically interfaced with the database, the machine learning execution tool configured to execute the one or more prediction models based on the one or more selected parameters and generate the prediction result based on execution of the one or more prediction models. 
 
     
     
       3. The computer system in accordance with  claim 2 , said query interface extension further configured to identify that one or more of the prediction models is executable using the one or more selected parameters. 
     
     
       4. The computer system in accordance with  claim 3 , wherein identifying the one or more of the prediction models comprises identifying required parameter inputs for each of the respective one or more prediction models. 
     
     
       5. The computer system in accordance with  claim 3 , said query interface extension further configured to invoke the machine learning execution tool using the one or more selected parameters and the identified one or more prediction models. 
     
     
       6. The computer system in accordance with  claim 1 , said query interface extension further configured to generate a resultant dataset, the resultant dataset comprising the obtained data and the appended prediction result, the appended prediction result being identified as prediction data. 
     
     
       7. The computer system in accordance with  claim 6 ,
 said query interface extension further configured to transmit the resultant dataset to the query interface for presentation via the query application. 
 
     
     
       8. A computer-implemented method executable on a computer system comprising a processor and a memory and in which a plurality of business intelligence (BI) data objects is persisted in a database stored in the memory, each BI data object being associated with one or more data parameters, said method comprising:
 intercepting, by a query interface extension, a data call from a query application to a query interface for data corresponding to one or more of the BI data objects, the data call including one or more selected parameters; 
 parsing, by the query interface extension, the data call to ascertain the one or more selected parameters; 
 obtaining, by the query interface extension, the data corresponding to the one or more BI data objects based on the one or more selected parameters; and 
 appending, by the query interface extension, a prediction result to the obtained data. 
 
     
     
       9. The computer-implemented method in accordance with  claim 8 , the computer system including one or more prediction models and a machine learning execution tool, said method further comprising:
 executing, by the machine learning execution tool, one or more of the prediction models based on the one or more selected parameters; and 
 generating the prediction result based on the execution of one or more of the prediction models. 
 
     
     
       10. The computer-implemented method in accordance with  claim 9 , further comprising identifying, by the query interface extension, that one or more of the prediction models is executable using the one or more selected parameters. 
     
     
       11. The computer-implemented method in accordance with  claim 10 , wherein the operation of identifying the one or more of the prediction models comprises identifying required parameter inputs for each of the respective one or more prediction models. 
     
     
       12. The computer-implemented method in accordance with  claim 10 , further comprising invoking, by the query interface extension, the machine learning execution tool using the one or more selected parameters and the identified one or more prediction models. 
     
     
       13. The computer-implemented method in accordance with  claim 8 , further comprising generating a resultant dataset via the query interface extension, the resultant dataset comprising the obtained data and the appended prediction result, the appended prediction result being identified as prediction data. 
     
     
       14. The computer-implemented method in accordance with  claim 13 , further comprising transmitting the resultant dataset to the query interface for presentation via the query application. 
     
     
       15. A non-transitory computer-readable storage medium having computer-executable instructions stored thereon for use in a computer system in which a plurality of business intelligence (BI) data objects is persisted in a database, each BI data object being associated with one or more data parameters, the computer-executable instructions, when executed by the computer system, causing the computer system to:
 intercept, by a query interface extension, a data call from a query application to a query interface for data corresponding to one or more of the BI data objects, the data call including one or more selected parameters; 
 parse, by the query interface extension, the data call to ascertain the one or more selected parameters; 
 obtain, by the query interface extension, the data corresponding to the one or more BI data objects based on the one or more selected parameters; and 
 append, by the query interface extension, a prediction result to the obtained data. 
 
     
     
       16. The computer-readable storage medium in accordance with  claim 15 , the computer system including one or more prediction models and a machine learning execution tool, the computer-executable instructions further causing the computer system to:
 execute, by the machine learning execution tool, one or more of the prediction models based on the one or more selected parameters; and 
 generate the prediction result based on the execution of one or more of the prediction models. 
 
     
     
       17. The computer-readable storage medium in accordance with  claim 16 , the computer-executable instructions further causing the computer system to identify, by the query interface extension, that one or more of the prediction models is executable using the one or more selected parameters. 
     
     
       18. The computer-readable storage medium in accordance with  claim 17 , wherein identifying the one or more of the prediction models comprises identifying required parameter inputs for each of the respective one or more prediction models. 
     
     
       19. The computer-readable storage medium in accordance with  claim 17 , the computer-executable instructions further causing the computer system to invoke, by the query interface extension, the machine learning execution tool using the one or more selected parameters and the identified one or more prediction models. 
     
     
       20. The computer-readable storage medium in accordance with  claim 15 , the computer-executable instructions further causing the computer system to:
 generate a resultant dataset via the query interface extension, the resultant dataset comprising the obtained data and the appended prediction result, the appended prediction result being identified as prediction data; and 
 transmitting the resultant dataset to the query interface for presentation via the query application.